calculate_metric

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It discloses exact decimal precision, that rates/margins are decimals (0.05 = 5%), optional defaults like [gross_margin=1], and that currency only formats monetary results. It does not discuss error handling or edge cases, but the provided behavior is substantial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every line earns its place. The intro is front-loaded, the metric-to-params list is well-structured with code blocks and bullets, and the Args section mirrors the schema. There is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (14 metrics, varying params), the description is thorough: it explains precision, param mappings, defaults, and formatting, and points to list_metrics for full schemas. Since an output schema exists, omitting return-value details is acceptable. This description is fully adequate for a complex compute tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates fully by mapping each metric to its required parameter keys, showing optional defaults in brackets, and explaining the decimal convention. It also clarifies that currency is for formatting. This gives the agent complete parameter semantics beyond the generic schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear verb+resource: 'Compute a business / SaaS / finance metric with exact decimal precision.' It then lists 14 supported metric names, giving a precise scope that differentiates it from sibling calculators like currency_convert or business_days.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly defines usage by listing the metrics it supports and directs users to call list_metrics for full schemas, but it never explicitly states when to choose this tool over alternatives like compound_growth, net_present_value, or currency_convert. There are no exclusions or trade-off notes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.